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Climate crisis and correlating prolonged, more intense periods of droughtthreaten tree health in cities and forests. In consequence, arborists andforesters suffer from increasing workloads and, in the best case, a consistentbut often declining workforce. To optimise workflows and increase productivity,we propose a novel open-source end-to-end approach that generates helpfulinformation and improves task planning of those who care for trees in andaround cities. Our approach is based on RGB and multispectral UAV data, whichis used to create tree inventories of city parks and forests and to deduce treevitality assessments through statistical indices and Deep Learning. Due to EUrestrictions regarding flying drones in urban areas, we will also usemultispectral satellite data and fifteen soil moisture sensors to extend ourtree vitality-related basis of data. Furthermore, Bamberg already has ageoreferenced tree cadastre of around 15,000 solitary trees in the city area,which is also used to generate helpful information. All mentioned data is thenjoined and visualised in an interactive web application allowing arborists andforesters to generate individual and flexible evaluations, thereby improvingdaily task planning.

Task Planning Support for Arborists and Foresters: Comparing Deep  Learning Approaches for Tree Inventory and Tree Vitality Assessment Based on  UAV-Data